A Clinical Score for Predicting Atrial Fibrillation in Patients with Cryptogenic Stroke or Transient Ischemic Attack

Cardiology. 2017;138(3):133-140. doi: 10.1159/000476030. Epub 2017 Jun 28.

Abstract

Objectives: Detection of atrial fibrillation (AF) in post-cryptogenic stroke (CS) or transient ischemic attack (TIA) patients carries important therapeutic implications.

Methods: To risk stratify CS/TIA patients for later development of AF, we conducted a retrospective cohort study using data from 1995 to 2015 in the Stanford Translational Research Integrated Database Environment (STRIDE).

Results: Of the 9,589 adult patients (age ≥40 years) with CS/TIA included, 482 (5%) patients developed AF post CS/TIA. Of those patients, 28.4, 26.3, and 45.3% were diagnosed with AF 1-12 months, 1-3 years, and >3 years after the index CS/TIA, respectively. Age (≥75 years), obesity, congestive heart failure, hypertension, coronary artery disease, peripheral vascular disease, and valve disease are significant risk factors, with the following respective odds ratios (95% CI): 1.73 (1.39-2.16), 1.53 (1.05-2.18), 3.34 (2.61-4.28), 2.01 (1.53-2.68), 1.72 (1.35-2.19), 1.37 (1.02-1.84), and 2.05 (1.55-2.69). A risk-scoring system, i.e., the HAVOC score, was constructed using these 7 clinical variables that successfully stratify patients into 3 risk groups, with good model discrimination (area under the curve = 0.77).

Conclusions: Findings from this study support the strategy of looking longer and harder for AF in post-CS/TIA patients. The HAVOC score identifies different levels of AF risk and may be used to select patients for extended rhythm monitoring.

Keywords: Atrial fibrillation; Cardiovascular risk and prevention; Cryptogenic stroke; Rhythm monitoring.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Aged
  • Aged, 80 and over
  • Atrial Fibrillation / diagnosis*
  • Atrial Fibrillation / epidemiology*
  • California / epidemiology
  • Coronary Disease / complications
  • Databases, Factual
  • Female
  • Heart Failure / complications
  • Humans
  • Hypertension / complications
  • Ischemic Attack, Transient / complications*
  • Logistic Models
  • Male
  • Middle Aged
  • Multivariate Analysis
  • Retrospective Studies
  • Risk Factors
  • Sensitivity and Specificity
  • Severity of Illness Index*
  • Stroke / complications*
  • Time Factors